chore: release v1.35.0

Add dense-modules layout for data-rich guides and 3 new styles:
morandi-journal, pop-laboratory, retro-pop-grid. Add keyword shortcuts
for 高密度信息大图 auto-selection.

Prompt credit: AJ (https://waytoagi.feishu.cn/wiki/YG0zwalijihRREkgmPzcWRInnUg)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.claude-plugin/marketplace.json

@@ -6,7 +6,7 @@
   },
   "metadata": {
     "description": "Skills shared by Baoyu for improving daily work efficiency",
-    "version": "1.34.0"
+    "version": "1.35.0"
   },
   "plugins": [
     {

CHANGELOG.md

@@ -2,6 +2,26 @@
 
 English | [中文](./CHANGELOG.zh.md)
 
+## 1.35.0 - 2026-02-24
+
+### Features
+- `baoyu-image-gen`: add Replicate provider support with configurable models (by @justnode)
+- `baoyu-infographic`: add `dense-modules` layout and 3 new styles (`morandi-journal`, `pop-laboratory`, `retro-pop-grid`) for high-density infographics. Add keyword shortcuts for auto-selection. Prompt credit: [AJ](https://waytoagi.feishu.cn/wiki/YG0zwalijihRREkgmPzcWRInnUg)
+
+### Documentation
+- `baoyu-image-gen`: add Replicate model configuration documentation
+
+## 1.34.2 - 2026-02-25
+
+### Documentation
+- `baoyu-markdown-to-html`: clarify theme resolution order with local and cross-skill EXTEND.md fallbacks before prompting user.
+- `baoyu-post-to-wechat`: align markdown conversion theme handling with deterministic fallback (`CLI --theme` -> EXTEND.md `default_theme` -> `default`) and require explicit `--theme` parameter.
+
+## 1.34.1 - 2026-02-20
+
+### Fixes
+- `baoyu-post-to-wechat`: fix upload progress check crashing on second iteration (by @LyInfi)
+
 ## 1.34.0 - 2026-02-17
 
 ### Features

CHANGELOG.zh.md

@@ -2,6 +2,26 @@
 
 [English](./CHANGELOG.md) | 中文
 
+## 1.35.0 - 2026-02-24
+
+### 新功能
+- `baoyu-image-gen`：新增 Replicate 图片生成服务，支持自定义模型配置 (by @justnode)
+- `baoyu-infographic`：新增 `dense-modules` 高密度模块布局及 3 种新风格（`morandi-journal`、`pop-laboratory`、`retro-pop-grid`），支持关键词快捷选择。高密度信息大图提示词来自 [AJ](https://waytoagi.feishu.cn/wiki/YG0zwalijihRREkgmPzcWRInnUg)
+
+### 文档
+- `baoyu-image-gen`：补充 Replicate 模型配置说明文档
+
+## 1.34.2 - 2026-02-25
+
+### 文档
+- `baoyu-markdown-to-html`：明确主题解析优先级，先读取本技能与跨技能 EXTEND.md 的 `default_theme`，仅在未命中时询问用户。
+- `baoyu-post-to-wechat`：统一 markdown 转 HTML 的主题解析回退链（CLI `--theme` -> EXTEND.md `default_theme` -> `default`），并强制始终显式传入 `--theme` 参数。
+
+## 1.34.1 - 2026-02-20
+
+### 修复
+- `baoyu-post-to-wechat`：修复上传进度检查在第二次迭代时崩溃的问题 (by @LyInfi)
+
 ## 1.34.0 - 2026-02-17
 
 ### 新功能

skills/baoyu-image-gen/SKILL.md

@@ -1,11 +1,11 @@
 ---
 name: baoyu-image-gen
-description: AI image generation with OpenAI, Google and DashScope APIs. Supports text-to-image, reference images, aspect ratios. Sequential by default; parallel generation available on request. Use when user asks to generate, create, or draw images.
+description: AI image generation with OpenAI, Google, DashScope and Replicate APIs. Supports text-to-image, reference images, aspect ratios. Sequential by default; parallel generation available on request. Use when user asks to generate, create, or draw images.
 ---
 
 # Image Generation (AI SDK)
 
-Official API-based image generation. Supports OpenAI, Google and DashScope (阿里通义万象) providers.
+Official API-based image generation. Supports OpenAI, Google, DashScope (阿里通义万象) and Replicate providers.
 
 ## Script Directory
 
@@ -71,6 +71,12 @@ npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provi
 
 # DashScope (阿里通义万象)
 npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope
+
+# Replicate (google/nano-banana-pro)
+npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
+
+# Replicate with specific model
+npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
 ```
 
 ## Options
@@ -80,7 +86,7 @@ npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "一只可爱的猫" --image ou
 | `--prompt <text>`, `-p` | Prompt text |
 | `--promptfiles <files...>` | Read prompt from files (concatenated) |
 | `--image <path>` | Output image path (required) |
-| `--provider google\|openai\|dashscope` | Force provider (default: google) |
+| `--provider google\|openai\|dashscope\|replicate` | Force provider (default: google) |
 | `--model <id>`, `-m` | Model ID (`--ref` with OpenAI requires GPT Image model, e.g. `gpt-image-1.5`) |
 | `--ar <ratio>` | Aspect ratio (e.g., `16:9`, `1:1`, `4:3`) |
 | `--size <WxH>` | Size (e.g., `1024x1024`) |
@@ -97,19 +103,46 @@ npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "一只可爱的猫" --image ou
 | `OPENAI_API_KEY` | OpenAI API key |
 | `GOOGLE_API_KEY` | Google API key |
 | `DASHSCOPE_API_KEY` | DashScope API key (阿里云) |
+| `REPLICATE_API_TOKEN` | Replicate API token |
 | `OPENAI_IMAGE_MODEL` | OpenAI model override |
 | `GOOGLE_IMAGE_MODEL` | Google model override |
 | `DASHSCOPE_IMAGE_MODEL` | DashScope model override (default: z-image-turbo) |
+| `REPLICATE_IMAGE_MODEL` | Replicate model override (default: google/nano-banana-pro) |
 | `OPENAI_BASE_URL` | Custom OpenAI endpoint |
 | `GOOGLE_BASE_URL` | Custom Google endpoint |
 | `DASHSCOPE_BASE_URL` | Custom DashScope endpoint |
+| `REPLICATE_BASE_URL` | Custom Replicate endpoint |
 
 **Load Priority**: CLI args > EXTEND.md > env vars > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`
 
+## Replicate Model Configuration
+
+When using `--provider replicate`, the model can be configured in the following ways (highest priority first):
+
+1. CLI flag: `--model <owner/name>`
+2. EXTEND.md: `default_model.replicate`
+3. Env var: `REPLICATE_IMAGE_MODEL`
+4. Built-in default: `google/nano-banana-pro`
+
+Supported model formats:
+
+- `owner/name` (recommended for official models), e.g. `google/nano-banana-pro`
+- `owner/name:version` (community models by version), e.g. `stability-ai/sdxl:<version>`
+
+Examples:
+
+```bash
+# Use Replicate default model
+npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate
+
+# Override model explicitly
+npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana
+```
+
 ## Provider Selection
 
-1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI
-2. `--provider` specified → use it (if `--ref`, must be `google` or `openai`)
+1. `--ref` provided + no `--provider` → auto-select Google first, then OpenAI, then Replicate
+2. `--provider` specified → use it (if `--ref`, must be `google`, `openai`, or `replicate`)
 3. Only one API key available → use that provider
 4. Multiple available → default to Google
 

skills/baoyu-image-gen/references/config/preferences-schema.md

@@ -11,7 +11,7 @@ description: EXTEND.md YAML schema for baoyu-image-gen user preferences
 ---
 version: 1
 
-default_provider: null      # google|openai|dashscope|null (null = auto-detect)
+default_provider: null      # google|openai|dashscope|replicate|null (null = auto-detect)
 
 default_quality: null       # normal|2k|null (null = use default: 2k)
 
@@ -23,6 +23,7 @@ default_model:
   google: null              # e.g., "gemini-3-pro-image-preview"
   openai: null              # e.g., "gpt-image-1.5"
   dashscope: null           # e.g., "z-image-turbo"
+  replicate: null           # e.g., "google/nano-banana-pro"
 ---
 ```
 
@@ -38,6 +39,7 @@ default_model:
 | `default_model.google` | string\|null | null | Google default model |
 | `default_model.openai` | string\|null | null | OpenAI default model |
 | `default_model.dashscope` | string\|null | null | DashScope default model |
+| `default_model.replicate` | string\|null | null | Replicate default model |
 
 ## Examples
 
@@ -62,5 +64,6 @@ default_model:
   google: "gemini-3-pro-image-preview"
   openai: "gpt-image-1.5"
   dashscope: "z-image-turbo"
+  replicate: "google/nano-banana-pro"
 ---
 ```

skills/baoyu-image-gen/scripts/main.ts

@@ -14,7 +14,7 @@ Options:
   -p, --prompt <text>       Prompt text
   --promptfiles <files...>  Read prompt from files (concatenated)
   --image <path>            Output image path (required)
-  --provider google|openai|dashscope  Force provider (auto-detect by default)
+  --provider google|openai|dashscope|replicate  Force provider (auto-detect by default)
   -m, --model <id>          Model ID
   --ar <ratio>              Aspect ratio (e.g., 16:9, 1:1, 4:3)
   --size <WxH>              Size (e.g., 1024x1024)
@@ -30,12 +30,15 @@ Environment variables:
   GOOGLE_API_KEY            Google API key
   GEMINI_API_KEY            Gemini API key (alias for GOOGLE_API_KEY)
   DASHSCOPE_API_KEY         DashScope API key (阿里云通义万象)
+  REPLICATE_API_TOKEN       Replicate API token
   OPENAI_IMAGE_MODEL        Default OpenAI model (gpt-image-1.5)
   GOOGLE_IMAGE_MODEL        Default Google model (gemini-3-pro-image-preview)
   DASHSCOPE_IMAGE_MODEL     Default DashScope model (z-image-turbo)
+  REPLICATE_IMAGE_MODEL     Default Replicate model (google/nano-banana-pro)
   OPENAI_BASE_URL           Custom OpenAI endpoint
   GOOGLE_BASE_URL           Custom Google endpoint
   DASHSCOPE_BASE_URL        Custom DashScope endpoint
+  REPLICATE_BASE_URL        Custom Replicate endpoint
 
 Env file load order: CLI args > EXTEND.md > process.env > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env`);
 }
@@ -108,7 +111,7 @@ function parseArgs(argv: string[]): CliArgs {
 
     if (a === "--provider") {
       const v = argv[++i];
-      if (v !== "google" && v !== "openai" && v !== "dashscope") throw new Error(`Invalid provider: ${v}`);
+      if (v !== "google" && v !== "openai" && v !== "dashscope" && v !== "replicate") throw new Error(`Invalid provider: ${v}`);
       out.provider = v;
       continue;
     }
@@ -250,9 +253,9 @@ function parseSimpleYaml(yaml: string): Partial<ExtendConfig> {
       } else if (key === "default_image_size") {
         config.default_image_size = value === "null" ? null : (value as "1K" | "2K" | "4K");
       } else if (key === "default_model") {
-        config.default_model = { google: null, openai: null, dashscope: null };
+        config.default_model = { google: null, openai: null, dashscope: null, replicate: null };
         currentKey = "default_model";
-      } else if (currentKey === "default_model" && (key === "google" || key === "openai" || key === "dashscope")) {
+      } else if (currentKey === "default_model" && (key === "google" || key === "openai" || key === "dashscope" || key === "replicate")) {
         const cleaned = value.replace(/['"]/g, "");
         config.default_model![key] = cleaned === "null" ? null : cleaned;
       }
@@ -323,9 +326,9 @@ function normalizeOutputImagePath(p: string): string {
 }
 
 function detectProvider(args: CliArgs): Provider {
-  if (args.referenceImages.length > 0 && args.provider && args.provider !== "google" && args.provider !== "openai") {
+  if (args.referenceImages.length > 0 && args.provider && args.provider !== "google" && args.provider !== "openai" && args.provider !== "replicate") {
     throw new Error(
-      "Reference images require a ref-capable provider. Use --provider google (Gemini multimodal) or --provider openai (GPT Image edits)."
+      "Reference images require a ref-capable provider. Use --provider google (Gemini multimodal), --provider openai (GPT Image edits), or --provider replicate."
     );
   }
 
@@ -334,22 +337,24 @@ function detectProvider(args: CliArgs): Provider {
   const hasGoogle = !!(process.env.GOOGLE_API_KEY || process.env.GEMINI_API_KEY);
   const hasOpenai = !!process.env.OPENAI_API_KEY;
   const hasDashscope = !!process.env.DASHSCOPE_API_KEY;
+  const hasReplicate = !!process.env.REPLICATE_API_TOKEN;
 
   if (args.referenceImages.length > 0) {
     if (hasGoogle) return "google";
     if (hasOpenai) return "openai";
+    if (hasReplicate) return "replicate";
     throw new Error(
-      "Reference images require Google or OpenAI. Set GOOGLE_API_KEY/GEMINI_API_KEY or OPENAI_API_KEY, or remove --ref."
+      "Reference images require Google, OpenAI or Replicate. Set GOOGLE_API_KEY/GEMINI_API_KEY, OPENAI_API_KEY, or REPLICATE_API_TOKEN, or remove --ref."
     );
   }
 
-  const available = [hasGoogle && "google", hasOpenai && "openai", hasDashscope && "dashscope"].filter(Boolean) as Provider[];
+  const available = [hasGoogle && "google", hasOpenai && "openai", hasDashscope && "dashscope", hasReplicate && "replicate"].filter(Boolean) as Provider[];
 
   if (available.length === 1) return available[0]!;
   if (available.length > 1) return available[0]!;
 
   throw new Error(
-    "No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, or DASHSCOPE_API_KEY.\n" +
+    "No API key found. Set GOOGLE_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, DASHSCOPE_API_KEY, or REPLICATE_API_TOKEN.\n" +
       "Create ~/.baoyu-skills/.env or <cwd>/.baoyu-skills/.env with your keys."
   );
 }
@@ -389,6 +394,9 @@ async function loadProviderModule(provider: Provider): Promise<ProviderModule> {
   if (provider === "dashscope") {
     return (await import("./providers/dashscope")) as ProviderModule;
   }
+  if (provider === "replicate") {
+    return (await import("./providers/replicate")) as ProviderModule;
+  }
   return (await import("./providers/openai")) as ProviderModule;
 }
 
@@ -436,6 +444,7 @@ async function main(): Promise<void> {
     if (provider === "google") model = extendConfig.default_model.google ?? null;
     if (provider === "openai") model = extendConfig.default_model.openai ?? null;
     if (provider === "dashscope") model = extendConfig.default_model.dashscope ?? null;
+    if (provider === "replicate") model = extendConfig.default_model.replicate ?? null;
   }
   model = model || providerModule.getDefaultModel();
 

skills/baoyu-image-gen/scripts/providers/replicate.ts

@@ -0,0 +1,203 @@
+import path from "node:path";
+import { readFile } from "node:fs/promises";
+import type { CliArgs } from "../types";
+
+const DEFAULT_MODEL = "google/nano-banana-pro";
+const SYNC_WAIT_SECONDS = 60;
+const POLL_INTERVAL_MS = 2000;
+const MAX_POLL_MS = 300_000;
+
+export function getDefaultModel(): string {
+  return process.env.REPLICATE_IMAGE_MODEL || DEFAULT_MODEL;
+}
+
+function getApiToken(): string | null {
+  return process.env.REPLICATE_API_TOKEN || null;
+}
+
+function getBaseUrl(): string {
+  const base = process.env.REPLICATE_BASE_URL || "https://api.replicate.com";
+  return base.replace(/\/+$/g, "");
+}
+
+function parseModelId(model: string): { owner: string; name: string; version: string | null } {
+  const [ownerName, version] = model.split(":");
+  const parts = ownerName!.split("/");
+  if (parts.length !== 2 || !parts[0] || !parts[1]) {
+    throw new Error(
+      `Invalid Replicate model format: "${model}". Expected "owner/name" or "owner/name:version".`
+    );
+  }
+  return { owner: parts[0], name: parts[1], version: version || null };
+}
+
+function buildInput(prompt: string, args: CliArgs, referenceImages: string[]): Record<string, unknown> {
+  const input: Record<string, unknown> = { prompt };
+
+  if (args.aspectRatio) {
+    input.aspect_ratio = args.aspectRatio;
+  }
+
+  if (args.n > 1) {
+    input.number_of_images = args.n;
+  }
+
+  input.output_format = "png";
+
+  if (referenceImages.length > 0) {
+    if (referenceImages.length === 1) {
+      input.image = referenceImages[0];
+    } else {
+      for (let i = 0; i < referenceImages.length; i++) {
+        input[`image${i > 0 ? i + 1 : ""}`] = referenceImages[i];
+      }
+    }
+  }
+
+  return input;
+}
+
+async function readImageAsDataUrl(p: string): Promise<string> {
+  const buf = await readFile(p);
+  const ext = path.extname(p).toLowerCase();
+  let mimeType = "image/png";
+  if (ext === ".jpg" || ext === ".jpeg") mimeType = "image/jpeg";
+  else if (ext === ".gif") mimeType = "image/gif";
+  else if (ext === ".webp") mimeType = "image/webp";
+  return `data:${mimeType};base64,${buf.toString("base64")}`;
+}
+
+type PredictionResponse = {
+  id: string;
+  status: string;
+  output: unknown;
+  error: string | null;
+  urls?: { get?: string };
+};
+
+async function createPrediction(
+  apiToken: string,
+  model: { owner: string; name: string; version: string | null },
+  input: Record<string, unknown>,
+  sync: boolean
+): Promise<PredictionResponse> {
+  const baseUrl = getBaseUrl();
+
+  let url: string;
+  const body: Record<string, unknown> = { input };
+
+  if (model.version) {
+    url = `${baseUrl}/v1/predictions`;
+    body.version = model.version;
+  } else {
+    url = `${baseUrl}/v1/models/${model.owner}/${model.name}/predictions`;
+  }
+
+  const headers: Record<string, string> = {
+    Authorization: `Bearer ${apiToken}`,
+    "Content-Type": "application/json",
+  };
+
+  if (sync) {
+    headers["Prefer"] = `wait=${SYNC_WAIT_SECONDS}`;
+  }
+
+  const res = await fetch(url, {
+    method: "POST",
+    headers,
+    body: JSON.stringify(body),
+  });
+
+  if (!res.ok) {
+    const err = await res.text();
+    throw new Error(`Replicate API error (${res.status}): ${err}`);
+  }
+
+  return (await res.json()) as PredictionResponse;
+}
+
+async function pollPrediction(apiToken: string, getUrl: string): Promise<PredictionResponse> {
+  const start = Date.now();
+
+  while (Date.now() - start < MAX_POLL_MS) {
+    const res = await fetch(getUrl, {
+      headers: { Authorization: `Bearer ${apiToken}` },
+    });
+
+    if (!res.ok) {
+      const err = await res.text();
+      throw new Error(`Replicate poll error (${res.status}): ${err}`);
+    }
+
+    const prediction = (await res.json()) as PredictionResponse;
+
+    if (prediction.status === "succeeded") return prediction;
+    if (prediction.status === "failed" || prediction.status === "canceled") {
+      throw new Error(`Replicate prediction ${prediction.status}: ${prediction.error || "unknown error"}`);
+    }
+
+    await new Promise((r) => setTimeout(r, POLL_INTERVAL_MS));
+  }
+
+  throw new Error(`Replicate prediction timed out after ${MAX_POLL_MS / 1000}s`);
+}
+
+function extractOutputUrl(prediction: PredictionResponse): string {
+  const output = prediction.output;
+
+  if (typeof output === "string") return output;
+
+  if (Array.isArray(output)) {
+    const first = output[0];
+    if (typeof first === "string") return first;
+  }
+
+  if (output && typeof output === "object" && "url" in output) {
+    const url = (output as Record<string, unknown>).url;
+    if (typeof url === "string") return url;
+  }
+
+  throw new Error(`Unexpected Replicate output format: ${JSON.stringify(output)}`);
+}
+
+async function downloadImage(url: string): Promise<Uint8Array> {
+  const res = await fetch(url);
+  if (!res.ok) throw new Error(`Failed to download image from Replicate: ${res.status}`);
+  const buf = await res.arrayBuffer();
+  return new Uint8Array(buf);
+}
+
+export async function generateImage(
+  prompt: string,
+  model: string,
+  args: CliArgs
+): Promise<Uint8Array> {
+  const apiToken = getApiToken();
+  if (!apiToken) throw new Error("REPLICATE_API_TOKEN is required. Get one at https://replicate.com/account/api-tokens");
+
+  const parsedModel = parseModelId(model);
+
+  const refDataUrls: string[] = [];
+  for (const refPath of args.referenceImages) {
+    refDataUrls.push(await readImageAsDataUrl(refPath));
+  }
+
+  const input = buildInput(prompt, args, refDataUrls);
+
+  console.log(`Generating image with Replicate (${model})...`);
+
+  let prediction = await createPrediction(apiToken, parsedModel, input, true);
+
+  if (prediction.status !== "succeeded") {
+    if (!prediction.urls?.get) {
+      throw new Error("Replicate prediction did not return a poll URL");
+    }
+    console.log("Waiting for prediction to complete...");
+    prediction = await pollPrediction(apiToken, prediction.urls.get);
+  }
+
+  console.log("Generation completed.");
+
+  const outputUrl = extractOutputUrl(prediction);
+  return downloadImage(outputUrl);
+}

skills/baoyu-image-gen/scripts/types.ts

@@ -1,4 +1,4 @@
-export type Provider = "google" | "openai" | "dashscope";
+export type Provider = "google" | "openai" | "dashscope" | "replicate";
 export type Quality = "normal" | "2k";
 
 export type CliArgs = {
@@ -27,5 +27,6 @@ export type ExtendConfig = {
     google: string | null;
     openai: string | null;
     dashscope: string | null;
+    replicate: string | null;
   };
 };

skills/baoyu-infographic/SKILL.md

@@ -1,6 +1,6 @@
 ---
 name: baoyu-infographic
-description: Generates professional infographics with 20 layout types and 17 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", or "可视化".
+description: Generates professional infographics with 21 layout types and 20 visual styles. Analyzes content, recommends layout×style combinations, and generates publication-ready infographics. Use when user asks to create "infographic", "信息图", "visual summary", "可视化", or "高密度信息大图".
 ---
 
 # Infographic Generator
@@ -20,8 +20,8 @@ Two dimensions: **layout** (information structure) × **style** (visual aestheti
 
 | Option | Values |
 |--------|--------|
-| `--layout` | 20 options (see Layout Gallery), default: bento-grid |
-| `--style` | 17 options (see Style Gallery), default: craft-handmade |
+| `--layout` | 21 options (see Layout Gallery), default: bento-grid |
+| `--style` | 20 options (see Style Gallery), default: craft-handmade |
 | `--aspect` | landscape (16:9), portrait (9:16), square (1:1) |
 | `--lang` | en, zh, ja, etc. |
 
@@ -49,6 +49,7 @@ Two dimensions: **layout** (information structure) × **style** (visual aestheti
 | `venn-diagram` | Overlapping concepts |
 | `winding-roadmap` | Journey, milestones |
 | `circular-flow` | Cycles, recurring processes |
+| `dense-modules` | High-density modules, data-rich guides |
 
 Full definitions: `references/layouts/<layout>.md`
 
@@ -73,6 +74,9 @@ Full definitions: `references/layouts/<layout>.md`
 | `ikea-manual` | Minimal line art |
 | `knolling` | Organized flat-lay |
 | `lego-brick` | Toy brick construction |
+| `pop-laboratory` | Blueprint grid, coordinate markers, lab precision |
+| `morandi-journal` | Hand-drawn doodle, warm Morandi tones |
+| `retro-pop-grid` | 1970s retro pop art, Swiss grid, thick outlines |
 
 Full definitions: `references/styles/<style>.md`
 
@@ -92,9 +96,23 @@ Full definitions: `references/styles/<style>.md`
 | Educational | `bento-grid` + `chalkboard` |
 | Journey | `winding-roadmap` + `storybook-watercolor` |
 | Categories | `periodic-table` + `bold-graphic` |
+| Product Guide | `dense-modules` + `morandi-journal` |
+| Technical Guide | `dense-modules` + `pop-laboratory` |
+| Trendy Guide | `dense-modules` + `retro-pop-grid` |
 
 Default: `bento-grid` + `craft-handmade`
 
+## Keyword Shortcuts
+
+When user input contains these keywords, **auto-select** the associated layout and offer associated styles as top recommendations in Step 3. Skip content-based layout inference for matched keywords.
+
+If a shortcut has **Prompt Notes**, append them to the generated prompt (Step 5) as additional style instructions.
+
+| User Keyword | Layout | Recommended Styles | Default Aspect | Prompt Notes |
+|--------------|--------|--------------------|----------------|--------------|
+| 高密度信息大图 / high-density-info | `dense-modules` | `morandi-journal`, `pop-laboratory`, `retro-pop-grid` | portrait | — |
+| 信息图 / infographic | `bento-grid` | `craft-handmade` | landscape | Minimalist: clean canvas, ample whitespace, no complex background textures. Simple cartoon elements and icons only. |
+
 ## Output Structure
 
 ```
@@ -176,7 +194,9 @@ See `references/structured-content-template.md` for detailed format.
 
 ### Step 3: Recommend Combinations
 
-Recommend 3-5 layout×style combinations based on:
+**3.1 Check Keyword Shortcuts first**: If user input matches a keyword from the **Keyword Shortcuts** table, auto-select the associated layout and prioritize associated styles as top recommendations. Skip content-based layout inference.
+
+**3.2 Otherwise**, recommend 3-5 layout×style combinations based on:
 - Data structure → matching layout
 - Content tone → matching style
 - Audience expectations
@@ -222,8 +242,8 @@ Report: topic, layout, style, aspect, language, output path, files created.
 - `references/analysis-framework.md` - Analysis methodology
 - `references/structured-content-template.md` - Content format
 - `references/base-prompt.md` - Prompt template
-- `references/layouts/<layout>.md` - 20 layout definitions
-- `references/styles/<style>.md` - 17 style definitions
+- `references/layouts/<layout>.md` - 21 layout definitions
+- `references/styles/<style>.md` - 20 style definitions
 
 ## Extension Support
 

skills/baoyu-infographic/references/analysis-framework.md

@@ -38,7 +38,8 @@ Approach content analysis as a **world-class instructional designer**:
 | **Cycle/Loop** | Recurring processes, feedback loops | circular-flow | craft-handmade, technical-schematic |
 | **System/Structure** | Components, architecture, anatomy | structural-breakdown, bento-grid | technical-schematic, ikea-manual |
 | **Journey/Narrative** | Stories, user flows, milestones | winding-roadmap, story-mountain | storybook-watercolor, comic-strip |
-| **Overview/Summary** | Multiple topics, feature highlights | bento-grid, periodic-table | chalkboard, bold-graphic |
+| **Overview/Summary** | Multiple topics, feature highlights | bento-grid, periodic-table, dense-modules | chalkboard, bold-graphic |
+| **Product/Buying Guide** | Multi-dimension comparisons, specs, pitfalls | dense-modules | morandi-journal, pop-laboratory, retro-pop-grid |
 
 ### 2. Learning Objective Identification
 

skills/baoyu-infographic/references/layouts/dense-modules.md

@@ -0,0 +1,72 @@
+# dense-modules
+
+High-density modular layout with 6-7 typed information modules packed with concrete data.
+
+## Structure
+
+- 6-7 distinct modules per image, each serving a specific information function
+- Every module contains concrete data: brand names, numbers, percentages, parameters
+- Minimal whitespace—compact spacing prioritized over breathing room
+- Smaller text acceptable to maximize information density
+- Each module identified by coordinate label or section marker (e.g., MOD-1, SEC-A)
+
+## Module Archetypes
+
+| Module | Purpose | Content Requirements |
+|--------|---------|---------------------|
+| **Brand/Selection Array** | Grid of options with recommendations | 4-8 items with icons, names, brief descriptions; highlight "best choice" |
+| **Specification Scale** | Quality/measurement gauge | 3-5 levels with precise numerical increments, quality indicators (emoji faces, checkmarks) |
+| **Deep Dive/Detail** | Technical breakdown of key item | Zoom-in callouts, internal components, cross-section or exploded view |
+| **Scenario Comparison** | Side-by-side use cases | 3-6 scenarios with specific recommendations and data per scenario |
+| **Identification Tips** | How-to checklist | 3-5 inspection methods: look/test/check/ask format |
+| **Warning/Pitfall Zone** | Critical mistakes to avoid | 3-5 pitfalls with consequences, 1-2 correct approaches; high visual contrast |
+| **Quick Reference** | Compact summary | Dense table, one-line summaries, decision flowchart, or key takeaways |
+
+## Variants
+
+| Variant | Focus | Visual Emphasis |
+|---------|-------|-----------------|
+| **Coordinate-labeled** | Precision and systematicity | Each module has alphanumeric coordinate (A-01, B-05, C-12), ruler/axis markers |
+| **Grid-cell** | Order and structure | Modules in strict rectangular cells divided by thick lines, Swiss grid feel |
+| **Free-flowing** | Organic density | Magazine-style layout with dotted frames, varying module sizes, connected by arrows |
+
+## Best For
+
+- Product selection guides and buying guides
+- Multi-dimensional comparison content
+- Data-rich educational materials
+- "Avoid pitfalls" / "complete guide" formats
+- Content targeting platforms like Xiaohongshu with high-density visual requirements
+
+## Visual Elements
+
+- Module boundary markers (thick lines, dotted frames, or coordinate grids)
+- Quality indicators per module (emoji faces, checkmarks, crosses, crowns)
+- Data callout boxes with highlighted numbers
+- Comparison arrows and progression indicators
+- Warning/alert visual markers for pitfall modules
+- Metadata in corners (page numbers, timestamps, small barcodes)
+
+## Text Placement
+
+- Main title at top, prominent and impactful
+- Subtitle with module count ("X大维度全面解析...")
+- Module headers inside colored badges or labeled frames
+- Body text compact, multiple columns within modules
+- Numbers highlighted with accent colors, slightly larger than body text
+
+## Information Density Rules
+
+- Every corner should contain useful information or metadata
+- No decorative-only empty space
+- Text size may be reduced to fit more content—information over font size
+- Each module must have specific data points, not generic descriptions
+- Balance between density and readability: dense but organized
+
+## Recommended Pairings
+
+- `pop-laboratory`: Technical precision with coordinate markers and blueprint grid
+- `morandi-journal`: Hand-drawn warmth with doodle illustrations and organic frames
+- `retro-pop-grid`: 1970s pop art with strict grid cells and bold contrast
+- `corporate-memphis`: Clean business feel for product comparisons
+- `technical-schematic`: Engineering precision for technical product guides

skills/baoyu-infographic/references/styles/morandi-journal.md

@@ -0,0 +1,60 @@
+# morandi-journal
+
+Hand-drawn doodle illustration with warm Morandi color tones and cozy bullet journal aesthetic.
+
+## Color Palette
+
+- Background: Warm cream/beige with subtle paper texture (#F5F0E6)
+- Primary: Muted teal/sage green (#7BA3A8) for headers and frames
+- Secondary: Warm terracotta/orange (#D4956A) for highlights and numbers
+- Line art: Dark charcoal brown (#4A4540)
+- Soft highlights: Pale yellow (#F5E6C8)
+
+## Visual Elements
+
+- Hand-drawn doodle illustrations with organic, slightly imperfect ink lines
+- Washi tape strip decorations (diagonal stripes pattern, beige and brown)
+- Rounded card containers for brand/option items
+- Hand-drawn rulers, scales, and progress bars with emoji quality indicators
+- Smiley/frowny faces as quality markers (😊✓ 😐 ☹️✗)
+- Dotted line frames around sections
+- Connecting arrows and dotted lines between modules
+- Corner decorations: tiny houses, stars, sparkles, clouds
+- Wavy line dividers between sections
+- Callout bubbles for tips
+- Magnifying glass icons for identification tips
+- Thumbs up/down icons (hand-drawn style)
+
+## Variants
+
+| Variant | Focus | Visual Emphasis |
+|---------|-------|-----------------|
+| **Cozy journal** | Maximum warmth | More washi tape, stickers, decorative doodles |
+| **Clean sketch** | Readability | Cleaner lines, less decoration, more structured |
+
+## Typography
+
+- Main title: Bold hand-lettered calligraphy style with decorative flourishes
+- Module headers: Clean handwritten text in white on dark teal rounded badge (#6B9080)
+- Body text: Neat handwritten print style, easy to read
+- Numbers: Highlighted in terracotta (#D4956A), slightly larger than body
+
+## Style Enforcement
+
+- All imagery must maintain hand-drawn/doodle aesthetic—no digital precision
+- Organic, slightly imperfect shapes throughout
+- Sketch-like quality with visible line weight variations
+- Warm and cozy journal feel, not clinical or corporate
+
+## Avoid
+
+- Flat vector icons or emoji
+- Clean geometric shapes
+- Stock illustration style
+- Strict grid layout
+- Pure white background
+- Digital/corporate look
+
+## Best For
+
+Product selection guides, lifestyle content, educational overviews, consumer-facing comparison content, Xiaohongshu-style posts

skills/baoyu-infographic/references/styles/pop-laboratory.md

@@ -0,0 +1,48 @@
+# pop-laboratory
+
+Lab manual precision meets pop art color impact—coordinate systems, technical diagrams, and fluorescent accents on blueprint grid.
+
+## Color Palette
+
+- Background: Professional grayish-white with faint blueprint grid texture (#F2F2F2)
+- Primary: Muted teal/sage green (#B8D8BE) for major functional blocks and data zones
+- High-alert accent: Vibrant fluorescent pink (#E91E63) strictly for warnings, critical data, or "winner" highlights
+- Marker highlights: Vivid lemon yellow (#FFF200) as translucent highlighter effect for keywords
+- Line art: Ultra-fine charcoal brown (#2D2926) for technical grids, coordinates, and hairlines
+
+## Visual Elements
+
+- Coordinate-style labels on every module (e.g., R-20, G-02, SEC-08)
+- Technical diagrams: exploded views, cross-sections with anchor points, architectural skeletal lines
+- Vertical/horizontal rulers with precise markers (0.5mm, 1.8mm, 45°)
+- "Marker-over-print" effect: color blocks slightly offset from text, postmodern print feel
+- Cross-hair targets, mathematical symbols (Σ, Δ, ∞), directional arrows (X/Y axis)
+- Microscopic detail annotations alongside macroscopic bold headers
+- Corner metadata: tiny barcodes, timestamps, technical parameters
+- High contrast between massive bold headers and tiny 8pt-style annotations
+
+## Typography
+
+- Headers: Bold brutalist characters, high visual impact
+- Body: Professional sans-serif or crisp technical print
+- Numbers: Large, highlighted with yellow or blue to stand out
+- Annotations: Ultra-crisp, small technical labels
+
+## Style Enforcement
+
+- Strictly systematic color usage: only teal, pink, yellow, charcoal—no rainbow palette
+- Sufficient fine grid lines and coordinate annotations throughout
+- Maintain tension between large impactful headers and small precise parameters
+- Lab manual aesthetic: mix of microscopic details and macroscopic data
+
+## Avoid
+
+- Cute or cartoonish doodles
+- Soft pastels or generic textures
+- Empty white space
+- Flat vector stock icons
+- Organic or hand-drawn imperfections
+
+## Best For
+
+Technical product guides, specification comparisons, precision-focused data visualization, engineering-adjacent content

skills/baoyu-infographic/references/styles/retro-pop-grid.md

@@ -0,0 +1,47 @@
+# retro-pop-grid
+
+1970s retro pop art with strict Swiss international grid, thick black outlines, and flat color blocks.
+
+## Color Palette
+
+- Background: Warm vintage cream/beige (#F5F0E6)
+- Flat accents: Salmon pink, sky blue, mustard yellow, mint green—all muted retro tones
+- Contrast blocks: Solid pure black (#000000) and solid pure white (#FFFFFF) used strategically for extreme contrast
+- Line art and outlines: Solid thick black
+
+## Visual Elements
+
+- Uniform thick black outlines on all illustrations, text boxes, and grid dividers
+- Pure 2D flat vector aesthetic with subtle screen print texture
+- Strict Swiss international grid: poster divided into square and rectangular cells by thick black lines
+- Black-background cells with white text for warnings or key categories (inverted contrast)
+- Geometric fill patterns in empty cells: checkerboards, diagonal lines, dots
+- Flat abstract symbols, warning signs, keyholes, stars, arrows
+- Vintage comic-style smiley/frowny faces for quality indicators
+- Colored cells used for breathing room—some with minimal/no content
+
+## Typography
+
+- Headers: Bold brutalist or retro thick display fonts, high legibility
+- Body: Clean sans-serif, structured typographic alignment
+- Decorative English text acceptable for stylistic labels ("WARNING", "INFO", "BEST")
+- All content text in specified language
+
+## Style Enforcement
+
+- Absolutely no gradients, shading, drop shadows, or 3D effects
+- Everything anchored in grid cells—no floating or unorganized elements
+- Maintain 1970s retro pop art and underground comic illustration feel
+- Visual density balanced with rhythmic grid—some cells intentionally sparse for contrast
+
+## Avoid
+
+- 3D rendering, realistic details, gradients, soft shadows
+- Soft, thin, or sketch-like pencil lines
+- Free-flowing, unorganized, or floating layouts (everything must be grid-anchored)
+- Pure white background canvas
+- Organic or hand-drawn imperfections
+
+## Best For
+
+Trendy product guides, design-conscious content, visually striking comparisons, content targeting design-savvy audiences, bold social media posts

skills/baoyu-markdown-to-html/SKILL.md

@@ -68,9 +68,24 @@ Use `AskUserQuestion` to ask whether to format first. Formatting can fix:
 
 **If user declines**: Continue with original file.
 
-### Step 1: Confirm Theme
+### Step 1: Determine Theme
 
-Before converting, use AskUserQuestion to confirm the theme (unless user already specified):
+**Theme resolution order** (first match wins):
+1. User explicitly specified theme (CLI `--theme` or conversation)
+2. EXTEND.md `default_theme` (this skill's own EXTEND.md, checked in Step 0)
+3. `baoyu-post-to-wechat` EXTEND.md `default_theme` (cross-skill fallback)
+4. If none found → use AskUserQuestion to confirm
+
+**Cross-skill EXTEND.md check** (only if this skill's EXTEND.md has no `default_theme`):
+
+```bash
+# Check baoyu-post-to-wechat EXTEND.md for default_theme
+test -f "$HOME/.baoyu-skills/baoyu-post-to-wechat/EXTEND.md" && grep -o 'default_theme:.*' "$HOME/.baoyu-skills/baoyu-post-to-wechat/EXTEND.md"
+```
+
+**If theme is resolved from EXTEND.md**: Use it directly, do NOT ask the user.
+
+**If no default found**: Use AskUserQuestion to confirm:
 
 | Theme | Description |
 |-------|-------------|

skills/baoyu-post-to-wechat/SKILL.md

@@ -196,20 +196,19 @@ B) Continue - provide HTML file manually
 
 **Skip if**: Input is `.html` file
 
-1. **Ask theme preference** (unless specified in EXTEND.md or CLI):
+1. **Resolve theme** (first match wins, do NOT ask user if resolved):
+   - CLI `--theme` argument
+   - EXTEND.md `default_theme` (loaded in Step 0)
+   - Fallback: `default`
 
-| Theme | Description |
-|-------|-------------|
-| `default` | 经典主题 - 传统排版，标题居中带底边，二级标题白字彩底 |
-| `grace` | 优雅主题 - 文字阴影，圆角卡片，精致引用块 |
-| `simple` | 简洁主题 - 现代极简风，不对称圆角，清爽留白 |
-
-2. **Execute conversion** (using the discovered skill):
+2. **Execute conversion** (using the discovered skill), **always pass `--theme`**:
 
 ```bash
 npx -y bun ${MD_TO_HTML_SKILL_DIR}/scripts/main.ts <markdown_file> --theme <theme>
 ```
 
+**CRITICAL**: Always include `--theme` parameter. Never omit it, even if using `default`.
+
 3. **Parse JSON output** to get: `htmlPath`, `title`, `author`, `summary`, `contentImages`
 
 ### Step 4: Validate Metadata

skills/baoyu-post-to-wechat/scripts/wechat-browser.ts

@@ -570,10 +570,7 @@ export async function postToWeChat(options: WeChatBrowserOptions): Promise<void>
     for (let i = 0; i < 30; i++) {
       await sleep(2000);
       const uploadCheck = await cdp.send<{ result: { value: string } }>('Runtime.evaluate', {
-        expression: `
-          const thumbs = document.querySelectorAll('.weui-desktop-upload__thumb, .pic_item, [class*=upload_thumb]');
-          JSON.stringify({ uploaded: thumbs.length });
-        `,
+        expression: `JSON.stringify({ uploaded: document.querySelectorAll('.weui-desktop-upload__thumb, .pic_item, [class*=upload_thumb]').length })`,
         returnByValue: true,
       }, { sessionId });
       const status = JSON.parse(uploadCheck.result.value);